from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 52.823419 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 3.545643 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 39.438890 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 43.309989 |
| KMeans_tall | 0.0 | 1.0 | 39.000246 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 15.023345 |
| KMeans_short | 0.0 | 0.0 | 16.721461 |
| daal4py_KMeans_short | 0.0 | 0.0 | 7.369816 |
| LogisticRegression | 0.0 | 1.0 | 3.427299 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 53.872494 |
| Ridge | 0.0 | 0.0 | 47.123034 |
| daal4py_Ridge | 0.0 | 0.0 | 14.009139 |
| total | 0.0 | 31.0 | 35.739804 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.133 | 0.001 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.482 | 0.001 | 0.276 | 0.002 | See |
| 1 | KNeighborsClassifier | predict | 0.155 | 0.014 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 0.089 | 0.000 | 1.743 | 0.160 | See |
| 2 | KNeighborsClassifier | predict | 27.947 | 0.314 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 1.745 | 0.012 | 16.020 | 0.209 | See |
| 3 | KNeighborsClassifier | fit | 0.131 | 0.002 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.484 | 0.005 | 0.270 | 0.006 | See |
| 4 | KNeighborsClassifier | predict | 0.165 | 0.008 | 1000000 | 1 | 100 | brute | -1 | 5 | 0.0 | 1.0 | 0.088 | 0.002 | 1.871 | 0.104 | See |
| 5 | KNeighborsClassifier | predict | 37.294 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 0.0 | 1.0 | 1.765 | 0.007 | 21.128 | 0.088 | See |
| 6 | KNeighborsClassifier | fit | 0.119 | 0.000 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.483 | 0.001 | 0.247 | 0.001 | See |
| 7 | KNeighborsClassifier | predict | 0.170 | 0.014 | 1000000 | 1 | 100 | brute | -1 | 100 | 0.0 | 1.0 | 0.089 | 0.000 | 1.898 | 0.161 | See |
| 8 | KNeighborsClassifier | predict | 36.971 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 0.0 | 1.0 | 1.805 | 0.009 | 20.481 | 0.103 | See |
| 9 | KNeighborsClassifier | fit | 0.120 | 0.000 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.486 | 0.003 | 0.247 | 0.002 | See |
| 10 | KNeighborsClassifier | predict | 0.175 | 0.001 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 0.088 | 0.000 | 1.985 | 0.012 | See |
| 11 | KNeighborsClassifier | predict | 13.499 | 0.037 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 1.758 | 0.009 | 7.679 | 0.045 | See |
| 12 | KNeighborsClassifier | fit | 0.120 | 0.000 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.484 | 0.001 | 0.247 | 0.001 | See |
| 13 | KNeighborsClassifier | predict | 0.186 | 0.003 | 1000000 | 1 | 100 | brute | 1 | 5 | 0.0 | 1.0 | 0.090 | 0.000 | 2.066 | 0.032 | See |
| 14 | KNeighborsClassifier | predict | 23.610 | 0.023 | 1000000 | 1000 | 100 | brute | 1 | 5 | 0.0 | 1.0 | 1.747 | 0.007 | 13.513 | 0.059 | See |
| 15 | KNeighborsClassifier | fit | 0.132 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.487 | 0.004 | 0.271 | 0.007 | See |
| 16 | KNeighborsClassifier | predict | 0.184 | 0.001 | 1000000 | 1 | 100 | brute | 1 | 100 | 0.0 | 1.0 | 0.089 | 0.001 | 2.066 | 0.022 | See |
| 17 | KNeighborsClassifier | predict | 23.556 | 0.028 | 1000000 | 1000 | 100 | brute | 1 | 100 | 0.0 | 1.0 | 1.838 | 0.063 | 12.816 | 0.441 | See |
| 18 | KNeighborsClassifier | fit | 0.056 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.101 | 0.002 | 0.558 | 0.013 | See |
| 19 | KNeighborsClassifier | predict | 0.021 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.006 | 0.000 | 3.763 | 0.541 | See |
| 20 | KNeighborsClassifier | predict | 25.222 | 0.073 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.258 | 0.001 | 97.780 | 0.477 | See |
| 21 | KNeighborsClassifier | fit | 0.057 | 0.000 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.100 | 0.002 | 0.572 | 0.015 | See |
| 22 | KNeighborsClassifier | predict | 0.029 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.005 | 0.000 | 5.412 | 0.454 | See |
| 23 | KNeighborsClassifier | predict | 33.013 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.261 | 0.002 | 126.602 | 0.829 | See |
| 24 | KNeighborsClassifier | fit | 0.057 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.101 | 0.001 | 0.563 | 0.011 | See |
| 25 | KNeighborsClassifier | predict | 0.029 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.005 | 0.000 | 5.388 | 0.661 | See |
| 26 | KNeighborsClassifier | predict | 33.103 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.306 | 0.002 | 108.076 | 0.530 | See |
| 27 | KNeighborsClassifier | fit | 0.056 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.100 | 0.002 | 0.564 | 0.015 | See |
| 28 | KNeighborsClassifier | predict | 0.014 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.005 | 0.000 | 2.817 | 0.282 | See |
| 29 | KNeighborsClassifier | predict | 10.516 | 0.021 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.258 | 0.001 | 40.821 | 0.211 | See |
| 30 | KNeighborsClassifier | fit | 0.056 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.100 | 0.001 | 0.559 | 0.012 | See |
| 31 | KNeighborsClassifier | predict | 0.023 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.005 | 0.001 | 4.354 | 0.456 | See |
| 32 | KNeighborsClassifier | predict | 18.674 | 0.010 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.261 | 0.002 | 71.579 | 0.646 | See |
| 33 | KNeighborsClassifier | fit | 0.056 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.100 | 0.002 | 0.563 | 0.015 | See |
| 34 | KNeighborsClassifier | predict | 0.023 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.006 | 0.000 | 4.239 | 0.388 | See |
| 35 | KNeighborsClassifier | predict | 18.711 | 0.010 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.306 | 0.001 | 61.057 | 0.238 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.955 | 0.029 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.740 | 0.012 | 3.995 | 0.075 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 8.328 | 5.530 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.490 | 0.007 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.119 | 0.003 | 4.130 | 0.105 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.951 | 0.042 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.764 | 0.012 | 3.863 | 0.082 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 5.981 | 3.826 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.866 | 0.011 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.214 | 0.005 | 4.046 | 0.107 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 2.950 | 0.033 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.720 | 0.010 | 4.099 | 0.075 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 4.890 | 2.493 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 3.029 | 0.018 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.628 | 0.009 | 4.826 | 0.073 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.016 | 0.061 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.765 | 0.015 | 3.942 | 0.111 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 3.030 | 1.623 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.860 | 0.007 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.122 | 0.002 | 7.062 | 0.144 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.072 | 0.112 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.754 | 0.008 | 4.072 | 0.155 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 3.066 | 1.869 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.607 | 0.010 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.226 | 0.005 | 7.120 | 0.150 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 2.955 | 0.013 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.772 | 0.007 | 3.828 | 0.037 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 3.280 | 1.707 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 5.488 | 0.059 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.634 | 0.007 | 8.656 | 0.136 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.235 | 0.009 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.464 | 0.015 | 2.661 | 0.085 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 18.482 | 16.424 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.025 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 32.141 | 15.053 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.206 | 0.021 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.458 | 0.014 | 2.630 | 0.091 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 19.762 | 17.922 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.026 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 23.645 | 9.543 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.196 | 0.009 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.453 | 0.014 | 2.639 | 0.085 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 18.164 | 15.177 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.045 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 7.221 | 0.930 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.192 | 0.006 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.457 | 0.017 | 2.611 | 0.097 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.474 | 5.125 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.024 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 30.974 | 14.041 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.199 | 0.007 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.451 | 0.012 | 2.657 | 0.073 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 5.486 | 5.208 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.025 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.001 | 21.965 | 11.809 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.204 | 0.013 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.448 | 0.015 | 2.685 | 0.093 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 5.117 | 4.571 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.056 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 8.389 | 1.358 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.578 | 0.008 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.392 | 0.023 | 1.476 | 0.090 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.281 | 2.227 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.149 | 1.898 | See |
| 3 | KMeans_tall | fit | 0.485 | 0.020 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 24.0 | NaN | 30.0 | NaN | 0.361 | 0.015 | 1.344 | 0.078 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.187 | 1.850 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.779 | 1.357 | See |
| 6 | KMeans_tall | fit | 6.310 | 0.079 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.035 | 0.013 | 2.079 | 0.028 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.514 | 1.095 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.842 | 0.988 | See |
| 9 | KMeans_tall | fit | 5.772 | 0.007 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.891 | 0.011 | 1.996 | 0.008 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.968 | 1.736 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.051 | 1.196 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.276 | 0.012 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 21.0 | NaN | 30.0 | NaN | 0.093 | 0.003 | 2.962 | 0.154 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.990 | 1.727 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.158 | 0.399 | See |
| 3 | KMeans_short | fit | 0.107 | 0.001 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.041 | 0.001 | 2.644 | 0.046 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.030 | 1.800 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.064 | 0.346 | See |
| 6 | KMeans_short | fit | 0.727 | 0.023 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 20.0 | NaN | 18.0 | NaN | 0.321 | 0.019 | 2.270 | 0.152 | See |
| 7 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.991 | 1.292 | See |
| 8 | KMeans_short | predict | 0.003 | 0.002 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 2.792 | 1.958 | See |
| 9 | KMeans_short | fit | 0.199 | 0.023 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 26.0 | NaN | 24.0 | NaN | 0.147 | 0.019 | 1.354 | 0.234 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.961 | 1.278 | See |
| 11 | KMeans_short | predict | 0.006 | 0.002 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 5.315 | 2.208 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 11.282 | 0.047 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 11.086 | 0.016 | 1.018 | 0.005 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.349 | 0.424 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.849 | 0.462 | See |
| 3 | LogisticRegression | fit | 0.860 | 0.018 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [28] | 0.780 | 0.025 | 1.102 | 0.042 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.001 | 0.084 | 0.118 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.003 | 0.000 | 0.563 | 0.145 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1.711 | 0.044 | 100000 | 100000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.834 | 0.003 | 2.052 | 0.054 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 100000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.665 | 0.791 | See |
| 2 | Ridge | predict | 0.001 | 0.000 | 100000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.001 | 0.000 | 0.801 | 0.458 | See |
| 3 | Ridge | fit | 1.154 | 0.011 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.221 | 0.001 | 5.229 | 0.056 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.637 | 0.761 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.725 | 0.609 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.12.so",
"prefix": "libopenblas",
"user_api": "blas",
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"version": "0.3.12",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
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}
],
"cpu_count": 2
}